Opening: 1 Postdoc in Machine Learning at Lund University (Sweden). *Position*: Postdoc *Research area*: Machine Learning *Duration*: 1 year renewable *Where*: Lund University - CS/Math departments *Application closing date*: December 3, 2019 *Head of group*: Professor Luigi Nardi (luigi.na...@cs.lth.se) *Apply*: https://lu.varbi.com/se/what:job/jobID:300056/
These projects, financed by WASP <https://wasp-sweden.org/> (Wallenberg AI, Autonomous System and Software Programme), aim at introducing innovative algorithms and methodologies to overcome the limitations of multi-objective black-box optimization. They are part of a collaboration with Stanford University. The students will be encouraged to apply to the WASP exchange program with Stanford to work closely with collaborators. Topics of interest: - Black-box optimization - Derivative-free optimization (DFO) - Bayesian optimization - Algorithm configuration and selection - Active learning - Automated machine learning (AutoML) - Neural architecture search (NAS) - Hyperparameter optimization - Learning to learn - Meta learning and transfer learning - Reinforcement learning (RL) - Optimization of neural networks - Evolutionary algorithms (EA) - Discrete optimization and NP-hard problem solving - Data-driven analysis of algorithms, hyperparameter importance, etc. Some applications of interest: Image classification, Natural Language Processing (NLP), Simultaneous localization and mapping (SLAM), Design space exploration (DSE), Optimizing compilers, Hardware design: CPU, GPU, FPGA, CGRA, ASIC.
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